0000000000309990

AUTHOR

Li You

showing 2 related works from this author

Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms

2021

This paper investigates the energy efficiency (EE) optimization in downlink multi-cell massive multiple-input multiple-output (MIMO). In our research, the statistical channel state information (CSI) is exploited to reduce the signaling overhead. To maximize the minimum EE among the neighbouring cells, we design the transmit covariance matrices for each base station (BS). Specifically, optimization schemes for this max-min EE problem are developed, in the centralized and distributed ways, respectively. To obtain the transmit covariance matrices, we first find out the closed-form optimal transmit eigenmatrices for the BS in each cell, and convert the original transmit covariance matrices desi…

Signal Processing (eess.SP)FOS: Computer and information sciencesmallintaminenComputational complexity theoryComputer scienceenergiatehokkuusComputer Science - Information TheoryMIMO02 engineering and technologyPrecoding0203 mechanical engineeringoptimointistatistical CSIalgoritmit0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringOverhead (computing)Electrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processingenergy efficiencymax-min fairnessInformation Theory (cs.IT)020206 networking & telecommunications020302 automobile design & engineeringmulti-cell MIMOCovarianceDistributed algorithmChannel state informationConvex optimizationdistributed processingAlgorithm
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Trajectory Design and Resource Allocation for Multi-UAV Networks : Deep Reinforcement Learning Approaches

2023

The future mobile communication system is expected to provide ubiquitous connectivity and unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which is prominent in its flexibility and low cost, emerges as a significant network entity to realize such ambitious targets. In this work, novel machine learning-based trajectory design and resource allocation schemes are presented for a multi-UAV communications system. In the considered system, the UAVs act as aerial Base Stations (BSs) and provide ubiquitous coverage. In particular, with the objective to maximize the system utility over all served users, a joint user association, power allocation and trajectory desi…

wireless networksreinforcement learningComputer Networks and Communicationssyväoppiminenmiehittämättömät ilma-aluksetcommunication systemsComputer Science ApplicationskoneoppiminenControl and Systems Engineeringtrajectoryresource managementautonomous aerial vehiclesthroughputlangattomat verkot
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